├── 01_regression_logistique_class_binaire.ipynb └── README.md /01_regression_logistique_class_binaire.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Régression Logistique", 7 | "provenance": [], 8 | "authorship_tag": "ABX9TyNfW1OLITzgfZTQ+mqA2JAg", 9 | "include_colab_link": true 10 | }, 11 | "kernelspec": { 12 | "name": "python3", 13 | "display_name": "Python 3" 14 | } 15 | }, 16 | "cells": [ 17 | { 18 | "cell_type": "markdown", 19 | "metadata": { 20 | "id": "view-in-github", 21 | "colab_type": "text" 22 | }, 23 | "source": [ 24 | "\"Open" 25 | ] 26 | }, 27 | { 28 | "cell_type": "code", 29 | "metadata": { 30 | "id": "71s3i8d3EPrx" 31 | }, 32 | "source": [ 33 | "import numpy as np\n", 34 | "import matplotlib.pyplot as plt\n", 35 | "from sklearn.datasets import make_blobs" 36 | ], 37 | "execution_count": 1, 38 | "outputs": [] 39 | }, 40 | { 41 | "cell_type": "markdown", 42 | "metadata": { 43 | "id": "Qg4pHgh3OSqn" 44 | }, 45 | "source": [ 46 | "#0. Dataset (Classification Binaire)" 47 | ] 48 | }, 49 | { 50 | "cell_type": "code", 51 | "metadata": { 52 | "id": "bXtZmqmeOPuz", 53 | "outputId": "b34fb774-6e8d-4a01-a897-6108875c61dd", 54 | "colab": { 55 | "base_uri": "https://localhost:8080/", 56 | "height": 283 57 | } 58 | }, 59 | "source": [ 60 | "X, y = make_blobs(n_samples=100, n_features=2, centers=2, random_state=0)\n", 61 | "y = y.reshape((y.shape[0], 1))\n", 62 | "plt.scatter(X[:,0], X[:, 1], c=y, cmap='bwr')" 63 | ], 64 | "execution_count": 3, 65 | "outputs": [ 66 | { 67 | "output_type": "execute_result", 68 | "data": { 69 | "text/plain": [ 70 | "" 71 | ] 72 | }, 73 | "metadata": { 74 | "tags": [] 75 | }, 76 | "execution_count": 3 77 | }, 78 | { 79 | "output_type": "display_data", 80 | "data": { 81 | "image/png": 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PmKGaLUr80Bh5CpGRwVDHiy/Wb8rh9bKXZaxISwMefJALm4FKkF4vQz1uDUEcdBCwYgUFvlatYhVp69aUV7Za5Kyp4Yfa+vVA797AiScmvoKn4g7UkacYEyYwm2LuXM4eKyqA0aMZq44lo0fzuvffz7BDdTVwxRUsTmoutbVcSFyyhL1KL7qo6XzxWNKjB7fG2LaNjnvHDsbWMzJYgDVvnvUaQm0tZYYnT6azv+IKfkA01/FXV/OcUP1elSTBKicx1luq5ZGvXy8yZoxIly4i/fuLzJzptEUimzaJLFgg8tNP8b1ueTmfR1FRZOeXlYmccIJIbi7zx30+kRYtRL74wl477ebMM0XS04PzzW+9NfjY2lqRSy+tn3/v84mMHh3+9TZsEDn9dF4zI0Nk+HCR7dvtux/FGaB55M6wcSNfo4uL6zJFvF7gr38Frr/eUdNcyYMPclbfsF/rEUckrshVWRlDLVaaLu3asclIIEuWAIMHBzck8Xopc9BURWxxMTsf7dhRV62akcHmIWvX6uzczageuUPcf399Jw7wP+iddyZ/82gR6pg88ADw9NMs4omWyZOtn9vGjcCmTdGPHwtCKU4C1s79vfes77Gykj9rildeoUxB4HWrq+tCakryYZsjN8akG2M+N8bMsmvMZGDRIuuiGGO46OUmmvPyVl0NDBtGKd9772WeeufOwEcfxc6+RF049PmAPn2C7cvMBC64IPj4Fi24ftGQrCz+rCnWrKEjb0hlJXXXleTDzhn5DQDW2jheUtCpk/X+ykq+Vic6NTV8q2jZktknWVl0TOecw9f0UEyZQkEp/8ywtJRvJhdcEJ3u+RVXWKf1HXwwPygSlUmT+Az9C5u5uUzJfPDB4GNHjrT+UDIGuPjipq/Vu7d1SmdmZuzE0RSHsQqcN3cD0BHA+wAGA5jV1PGptNg5dy4FnQIXubKzRUaMcNqy8LjhhmD7/UJV+fkiGzdan3fiicHnACJ5eSJLl0ZuT1kZx87NFUlL478tW4qsXs1FwkmTRHr04L4hQ0RWrYr8WnazZ4/IE0/wmU6ZwnsJxZw5IgUFfMb5+fz6vffCu05pqUinTlzk9D/3rCyR3r0jFypTEgOEWOy0y5G/DqAPgFNCOXIAYwEsA7Csc+fOcbrtxGDiRGZW5ObSiV90kUhxsdNWNc2+fXUKg1ZbZqbIuHEi774rctRRvLdDDxV56SWRk06KjSMXocOeN0/kgQfouP3P8i9/Cf7Qyc0VWbMm+mfhBOXlvM/33xepqGjeuT/+KDJqFLNd8vNFrr5aZO/e2NipxI9QjjzqrBVjzDkAzhaRa40xpwC4RUTOaeycVMpa8VNVxQW5Nm34iu0G1qyhOmJRUehjDjsM2LKlvniU18sQwPTpwbHaAw5g4Uy4XX7CpayMz7ZhpkdaGrXFX33V3uspihPEMmtlIIDzjDEbAbwCYLAx5iUbxk0qMjPp9NzixAHG9xsThkpLY4pbQwXA0lKWrw8ezHh6ejr/zc1lMwu7nTjAD0mrtLraWnYWUpRkJurKThEZD2A8AATMyEdHO64Se0SAL75gHnOfPiwvDyQvDxg3DnjqqeCZLsCOPKFkXHfvBqZO5fgLF3K2fPHF4WVdRMKBB3IB2YpDD43NNRUlUdA88hTlxx+Z3TBwIB1sx47An/4UfNxDDwH33ENHDNSVe3frBvz3v6FbmuXlcRY+cCDwxz8CY8fGzokDHHvUqOCMFq8XuPvu2F1XURIBWx25iCxoKj6uJAbnn88OQSUlwN69LED5xz+AmTPrH5eWBtx+O1BYyBl8RQWwaxflcAcPZrFPQ60Qr5cFT7EIoTTG009TNtfjYZrkQQdRIGzQoPjaoSjxRkv0U5Dvvwd69rQOi5x8MrBgQfPGe/ll4LbbKAzVqhWd+I03OlegU1HBnPVWrRq3obaWlZIffsjQzCWXBIeXFCWR0FZvyv+zZ099De1Adu5s/nijRnGrrOSirtMVltnZ1pWRgVRUAGecwZZtxcV8ixg/niXs/fvbZ0ttLd9kVN9EiSUaI09Beva0DntkZ7OsPlKyspx34uHy1FPA8uV04gAXc4uKuF5gx0vqrl2c4efk8LkOHmzdnUlR7EAdeQqSlQU8+SRnoX6H7vEwxzvWuuSJwqRJ1pk4u3ZFr6IoApxyCrsEVVVRkmDhQmDAAHe2tVMSH3XkKcqoUXQuo0bR6dx7L7vctGrltGWxpaiI6ZaNLcRGGwZZtIjrEIE5+LW1XJN48cXoxlYUKzRGnsL07Utxq1Rg924Kbv3vfwz/5ObWdUgKpH37prv9NMU331hL15aWAqtXRze2olihjlxJCc4+m/01/UVDFRWceXs8lNzNzuYC8IwZ0cf5e/WynvH75WwVxW7UkStJz+rVrDBtWPlpDB18//5cHxg+nM42WgYM4ILyypV1M/70dBZJjdaaZyUGaIxcSXo2bWJaZEOqq1kMdcstdLB2OHGAHxDz5gG/+Q1QUMBZ//Dh1Hyx0glPdLZtY1iqbVuga1c2zLbqbKQ4h87IlaTnmGOsW6fl5LAAKhbk5gKPP87NzezZAxx3HOsLqqspkvbnPzNMpYqSiYPOyJWkp1Mn4LLL6ksJ+EMd11zjnF1uYOJEYN+++jPw0lLg7beBdeucs0upjzpyJSX4z3+Av/2NYl/t2gFjxnBW6RcDU6xZvNhayiEzk2sASmKgoRUlJUhLA667jpsSPocfDrz7bvBCcW0t4+VKYqAzciVq9uwB/vUv4Mor+a9WLyYP117LSuBAMjOZa6+plImDOnIlKr7/np2Pxo9n2fv48fx+wwanLXMvIsD69YxBOyBOWo/OnSkkdvjhdOhZWcBZZ3GfW3R1UgF15EpUjBtHfRK/bklpKb8fN85Zu9zKypVA9+7A0Ucz2+aww6jQ6CQDBgBr1zINcdcuatar3G9ioXrkSlRkZlrnFGdkNN7vUwmmqIgZNnv31t9fUABs3swsGyW1iVnzZWNMjjHmM2PMKmPMV8YYi4ZhSrJiVWjT2H4lNNOnW38oVlcDr70Wf3sasmcP8PHHwA8/OG2J0hA7QisVAAaLyDEAegMYYoyxUZpfSWRGjQpeDMvKAi691Bl73MyPP1qn+pWV8WdOIQLcdRe7KJ19Nhc6hwzhG4SSGETtyIXsl+dH5v7N4SUapbaWMrWvvhrbGdQjjzCW6/PVbUcfDTz6aOyumawMGBDc/xTgvhNOiL89fqZOBSZMYHWsv7/rggXsj6okBrbEyI0x6QCWA+gG4AkRud3imLEAxgJA586d+2zatCnq6yrWbNwInHpqXdu2qirqfvzrX7HJNBABPvmEC2JHHEGHZMt1du7koF26MHic5Ijw9/bZZ3Uzc48H6NcPmD/fuSyRY46h6FhDsrOp7V5Q0Pwx9+4F3nyT4ZrTT6dipNI0oWLkEBHbNgAtAMwH0Kux4/r06SNK7Dj6aJG0NBG6Bm4+n8jLLzttWZjU1Ihcf71IdrZIQYFITo7IueeKlJSEP0ZtrcjChSJTpoisXRu5LevXi1xyiUi7diJHHCHy3HMcO0aUl4s8/LBIr14iPXuK/POf3OckBx5Y/2/Jv3k8Ips2NX+8hQtFcnP5N5mdzXHGjo3pY00aACwTK99rtTOaDcA9AG5p7Bh15LFj3Tr+x7D6j3fCCU5bFyb//reI11vf+JwckSuvDO/8bdtEunent8jN5QO5+GKRqqpGTysqEpk1S2TePJHKShHZvFmkRYv6n4per8jtt0d/jy5izBiR9PTgv6f27fmZ2xwqK0VatQoey+cTmTkzNvYnE6EcuR1ZK22NMS32f+0BcAaAr6MdV4mMkhKm/lmxb198bYmYRx4JbqhZXg5Mmxbc0seKUaNYkVRczK2sDJg1C/j3v0Oe8tJL7A40ahQwYgT1ybfd/E8+0MB2P6WlwEMPsazx+eetWwElGX/+M5CfX5eJZAzj9k891XjLPCs++sg6M6ekhI9TiQw7slYOBDDfGPMFgKUA3hORWTaMq0TAkUdap/7l5LBDvCvYtct6f22tdcfkhud+/HGwtygtpeex4NtvgbFjeci+fdx27QJ+fv1D62R4ESpuXX99SnSK6NqVzTnGjQOOPRa44ALG7IcPb/5YNTWhf6Ya55ETtWiWiHwB4FgbbFFsICMDmDwZGDmSQkfV1cwk6dgRuOEGp60Lk1NPZflgw4X4jh2BFi0aP7esLPQ0McSHwKRJ1v56fVo3HC2fIy1UQkBJCfDWW/RyRx3VuF0up0MHezKRBg60lh3w+ahIqUSGlugnIeecw7Lu3/+eYYIJE/h9fr7TloXJ3//OMkb/q0VaGt/ln3666dSNgw6i12lIVhYfhgW7dlnPBh/NuA21mZ6m7V28uOljrPjpJ8Yatm+P7HwXkpMDvPwys3Gys7nP52PmyoUXOmubq7EKnMd608XOxKOyUuSdd5jZsnWr09YI0yF+/3uRPn1ELrtMZOXK8M/96CMucmZl1a2kdekiUlhoefjs2Tyk4QJcTo7I9olvixx0kEhGhvUKcl6eyIwZzbu3ykquIPqzcrKzRa64osnF2GRiyxaRhx4SueMOkQULNGMlXBCvrJVwNnXkicWqVSJt29In5ebSr9x9t9NWRcnmzSJ33cXUwSefFCkuDnloTY3IWWfVd+Y+n8j48QEHrFgRnEljDB9cRUXzbLvjjuDUIo+H9ipKI4Ry5CqaleLU1rLWZtu2+vt9PhZsnHGGM3bFm5oa4I03+Nrv9bKAavDgBgfNn0/tAX8mS4cOjJEfeWTzLlZQYJ1C1LJl6IVeRUHogiB15CnOxx+H1s0YMYLOTQmgthb46ivG3Lt3b365pQgbhlr9v0tP19QNpVFipn6ouJuSktC+KClFkVavZkpPjx78pFqxonnnp6UxQ6VHj8hq5o0J3VrnF79o/niKAnXkKc8JJ1hPAn0+4JJL4m9PTFmyBOjfH3j9dSaPv/UWcNJJVICKJ48/zgecns7v09P5fSMFS0qc+Pln4JtvXPdmpI48xfH5mNXn8dT5FZ+PQklJV+ty443MJfdXY4rw+3h3ZD7+eGDZMuDyy1lh86tf8c2gb7AWkhIndu9mjLFzZ74xtW9P6VCXoDHyFGXNGuDhh/lv//7A0KHAf/8LFBYCw4Yx6pB0zSGyskK3LaqurvskU1KPQYP4xlZZWbfP6wU++IAfvAlCqBh51JWdivtYsICOu6KC2RrLlwMvvED51O7dnbYuhrRqZV18k5/ffNEQJXlYv55vSIFOHGCV8MMPJ0Z7pibQv94U5OqrGVHw615UVTEb7tZbnbUr5tx0U3DnBq+XoRW3t4Tfto2NPZXms21bcJsrgKG3jRtDn1dTA8ydCzzzDGdBDkQ3/OiMPMUoKqIwYENE4r/mF3duvZUz8qee4n/cykoKfNx3n9OWRc633zILZ+1afhh17UqVyN69nbbMPRx1lLWqZnY2cNpp1uds28ZwzM8/MyxnDGOUs2dThyDO6Iw8xcjODh0KjqTTi6tIS6NE7k8/sQ/etm1c6Q2l+5volJcz62bVKjqi8nLg66+BU05h6x0lPFq0AO64g6v8fjIyGHK76Sbrc664grP1oiKGYEpLWZTx4IPxsDgIdeQphr8xsl+wyI/X6yJ1xGgpKOCMtWVLpy2Jjpkz6UQavtJXVXFWroTPPfdwoahfP+Dgg6lrvHIl0K5d8LHFxXx9bajJW14OPPdcXMxtiEunIko0PPEE3wg/+IAOvbycEYZQkw8lQdm6lb+8hpSWxrbjdjJiDHDRRdyaorEc81BZUTFGHXkK4vUylLdxI7cjjmDarOIy+vWzTqnMzWUHbCU2tGgB9OzJGXsgmZkhpZJjjYZWUpiuXRlOTRonXlLC6shf/pJFNkuXOm1RbBk4kM7cE6CZnpMDHHYYcPbZztmVCkyezBCd/9n7u7c88IAj5kQ9IzfGdALwIoD2AATAsyLyWLTjKkqzKCqiVsnmzQwtpKWxFP/xx4Err3TauthgDPDuu+wc8vzzfOW/7DLg9tvdu4DrFo4+mvnnkyczc6h/f2YPecJoRBIDoq7sNMYcCOBAEVlhjMkDsBzA+SKyJtQ5Wtmp2M5DDzGNsKys/v7cXC4IOPQfTFHsJGbqhyLyo4is2P91EWQ9/dQAABlgSURBVIC1ACx6bSlKDHnzzWAnDnBmvnx5/O1RlDhia4zcGNMVbMS8xOJnY40xy4wxywoLC+28rKKw/N6KmpqmGzYrSjzYtw/44gsKdNmMbY7cGJML4A0AN4pIUPsTEXlWRPqKSN+2bdvadVlFIddfH1x+n5ZGNbuePZ2xyS189BHwu98B11zDQikHS80dYfduOtji4tiMX1sL3HILswpOOokNwq+5xlapXFscuTEmE3TiU0Vkhh1jKkqzOPNM4M47mbWRn8/Y+KGHAu+8434dlVhy2218ds88Azz7LNXUrr/eaaviQ1UVe/oddBAdbLt2/Buy+4Ps0UcpC1Fezll5eTkwZQqLkGzCjsVOA2AygF0icmM45+hip2KJCGeH06czP3r0aAqjN4edOylg1KYN9b3ViYdm7VpqbzdcW/B6gcWLqZXuxz97TKZsmD/8gRINgffv9XLhfNw4+65z4IGUhWhIXh6wd2+z/kZj2eptIIAxAAYbY1bu3zSJVWkeIny9HzKEueCPPML2RX//e/PGad0aOOsspiI64cTLytjB+cEHqYznb2KRiMyeHVxmDlC35b//5ddbtnCW7vFwGzqUFaVup6aGbyENP8RKS+nI7SRUQ+3iYuvnHwFRf7yKyGIAOu1RouPTT/m6WVrK7/3de+67Dxg1CujUyVHzwuK774ATT6TdZWV0fIcfTl2OQEGmRCGwLVQgGRm0t6KCFaI//ljncObMYc70+vXW0q9uoaLCWvEQAHbssPdaffoAn3wSvP/ww217w9HKTiUxmDHDOn3QGM4c3cDo0Wyx5J9pFRcDX37pmCJek1x4ofX+tDTg4ouZ0rlnT/1ZY00NwwFvvRUfG2OFxwN06WL9s3797L3WhAkM2fiblxjD723s0aqOXEkMcnKsZ4dpadb6zhs2AG+8wc4udixOVVZSDjbS5gy7dlF7o6Et5eXAiy9Gb18saN+eb0FeL+O1eXl0cBMn8g3ou+8oe9CQkhJWM7oZY6ge5/XWheDS0vgm8vDD9l6rXz+2kbvwQsonnHcesGhRaK3zSBCRuG99+vQRRanHmjUiHo8IXWHd5vGI7NxZd1x1tchll4nk5Ijk54v4fCLHHiuyY0fk154yRaSgQCQvj+OeeKLI9u3NG2PHDpGsrGD7AZEOHSK3LZCSEpHNm0WqquwZz8/evSKvvCIybZrI7t11+2fM4DNpeD95eSJvvhn++Lt2iTz0kMiwYSJ33CHyww/22h8Nn34qcu65It26iVx6qchXXzltUaMAWCYWPlUduZI4PP44HanPJ5KbSyf+1lv1j3nkERGvt75jycwUGTo0smt++mnweBkZIn37Nn+svn1FjKk/Vna2yO23R2abn8pKkWuv5fPweERatBB55pnoxgyHqiqRww7j8w181t27h/9hsnmzSLt2dR/SWVn83S5ZElvbkxR15Io7+PFHkeee4yw5cHbo55BDrGe9WVmcWTaXkSODnS9A575mTfPG+vprkTZt6KgA/tu7t0hRUfPtCmTcuOC3Fa83+EMuFuzYIXLllZyF5+Xx6+a8/YwZI5KeHvx8e/WKnc1JTChHHnUeeSRoHrkSMe3bUwSrIdnZwKZNoTV5RYD584GpUxkLvewy4OSTmWXy8cfBxxcUcLHv1FObZ19JCfPgN21iHvuQIaF764VDWRlTKq0Wgvv04RpBItO6tXX6XWYmf48qn9AsQuWRJ1F2v5ISnHMOFw8bljd36mTdlsvPuHE8r6SEi1vTpgG//S2rGlesCO60U1FRvyAmXHw+9nO0i507Q//MDV2AvF5rR25McL9BJWI0a0WJLXYXxDzwAKs2/bK0mZl0ni+8ELoAaMUK6kb7MzBE+PUzzwCnn85ZY2BOtM/HUu1EmC0ecIC1BK8x9qfJxYLf/S7Y/szMuiIjxRbUkSux4bnnqGGRns7OKZMn2zPugQeytPzPf+bs/PrrgdWrGSIJxTvvWBd/VFezFP3zz4Ebb2TPu0GDGH656y577I2WjAxWtwYKgvnzkP/yF/uvJ8LUwvXr7UnrvPVWdivyeKiB4/OxKcPEidGPrdRhFTiP9aaLnUnO888HZ4J4vSIvveSMPQ8/zOwRq9TGxx93xqbmMnOmSJ8+zAAZOlRk5Ur7r/HppyJduvB35fGI9Oghsnq1PWN/843Ia6+JLF0qUltrz5gpCHSxU4kbHToA27YF7+/aFfj++7ibg61bgW7dguPgHg+7TzcWW08Vdu4EDj6YLfMCad2aRVIaBkkIYimapSh1iFg7cSDyqslo6dCBC50eT10Fo9dLcSt14mTaNGt97MrKxsvxP/2U6wzt2zO89f77TV+rqgp47DHqxHfvzjCZVQWpEjaataLYizFs5mCVUXHwwcH7KiqY5rd6NUWELrwwNrO/iy5ihsrcubTxl7+kQ1fI1q3WKY4VFRTNsmLRIipN+oXOfv6Z5edTpwLnnx/6WiNGAB98UHfeX//Kv4GlS5NLJjeeWMVbYr1pjDzJmTo1OEbu8YhMn17/uJ9+EunatX4BzYEHJlYJd6owa1bd7yFw8/lEPvnE+py+fa2Ls7p2DX2dpUuD/zb8v/s33ojNvSURCBEj19CKYj+jRgHPP88OPRkZFAqaMiVYbe+mm6h37W+xVVzMWd0118Tf5lRnyBCgV6/6b0NeL4umjj/e+pzVq633//BDaInYTz6x1uAuLgY+/LB5Niv/j77HKLFh5EhujfHWW8Fx2Zoaal7X1tbJfiqxJz2dla//+hfXE9LT2QbtmmtC5+e3b28dQsvNDa1V3qEDf9bQ0Xs8DMkpEaH/UxTnCOWotT2bM+TksIfnl19S0ve661i8E4q77gpueO31stFwqN/hOefQaTf8eUYG9dyViLCr+fLzxpifjTFf2jGekiJcfHHwzC0jAzj3XJ2Nu4Hf/Aa4917OwDMy6sru09KCUz39ZGUxhHLUUfzg8Hq5CP7ee0DbtvG1P4mwJY/cGDMIQDGAF0WkV1PHax65AoAaHCedxLREf2u0Nm0YRw0UvyopYcu3yZMZehk+nJkOdvzH37KFKXMFBYwTWzWxCKS2lg5L3xpIbS1bv33xRV24xOOhoNeiRY0/p82bmYp48MH6PMMkpqJZIrLIGNPVjrGUFKJVKzqAOXP4Ot+jBzU4AlPQRIAzzmAZvX+W9+KLTF9bs6Zpx9sY99wD/OMfdbPJ9HTaYqVh8t131A2ZP5/HjxzJeHIi6LE4yZw5lEwIjHmXlbFb0oIFjatHuqEPq0uI2/urMWasMWaZMWZZYWFhvC6rJDrp6dTiuO02YNiw4Dzijz6isw98Va+qYm/M6dMjv+6CBWzpVV7OjImiIvanHDo0eAF21y7OOj/4gDPQykrg1VfZqsuByuiEYsmSuqyjQMrK+DMlLsTNkYvIsyLSV0T6ttVYmBIuK1eGTleLJjz37LN1BSmBVFYyJBDIpEl0TIFOu7KS4lJW3dFTiY4dKYTVEI+HP1Pigq4oKYnNIYdYZ054vSzvjpTGSsIbVjiuWmVd9SgCfP115DYkAyNHBv9+/IueI0Y4Y1MKoo5cSWzOPJMLoIEhF7+jiCZd7YILrHOdq6spZRtInz7BaXZ+evaM3AanqKoCduywRys+Lw9YuJALlhkZ3Hr04FtNqGem2I5d6YfTAHwCoIcxZosx5td2jKsoSE9nnPz00+scxfHHsz1bQUFkY5aXc6GyYcgmIwN48slgDZZf/Yrhg8CWbdnZ1NV2Q3MHP7W1wN13c5G5Y0cKhj36KEXOIo31i/CZbd/O55mWxjZ3q1bZa7vSOFZ1+7HeVGtFiYjSUpHi4ujHeeYZa72PnByRffusz/n+e5HzzqOueV4eu9rv20cdkpkzRbZvj96uWHP33db3nZkp0q2byMcfN3/MefOox2Kl9b5nj/33kOJAtVYU1+PxWC+sNZfp060XOrOyrBsxA9RSnzmTs/l9+9j55rjjmBo5ZgzQpQtnu4lKdTUwYYL1fVdVAevWURFy69bmjfvyy9brDRkZVJpU4oI6ciX1aNXKer8I25GFw7nnAhs2MHtm3z46+EcfBd5+2z477aS4OLSQlZ+qKmbzNIf09NDFPFqdGzf0SSupx+9+Z70Q16JFaKW/QL75hk684WJhSQlj74lIfn7TxUsVFZyZN4cxY6z142tquFCtxAV15ErqccopDINkZ9PB5eWxqfP//hfeLHLv3tANEHbvttVU20hLAx56qPFMEp8vOGOnKU46iR+MHg9DU14vv542jRosSlzQnp1KYiNCTY6cHPvbshUWAosXAy1b0iEFZqU0RkUFdV4a9rfMyWHZ//jx9tppJzNn0sa1azlr9r9VZGUBBx1EqYRI1iHWrgXeeYfnXnCBCmDFiFBaK+rIFefYtw945RVqWvfrx/L4QGe6eDFw+eXATz/R4fTty+MToWJw2jSq/5WX0zavl3YtXRp+nN1JqqsZBnr6aS6AjhhBB9+mjdOWKY2gjlxJLFav5mt8ZSUdSW4uOwktWsSvt2xhD8/AjIj0dGaHfPddYiykrVoFPP44Mz2GDgWuuMKerBpFCUFM1Q8VpdmMGkWRKj/FxXw9/9vfgAceAP7zH+vuQYWFrCRsTFUvXhxzDO1UFIdJgGmNknL8+CNn1Q0pLwdeeolfr19vnS7nj5krivL/qCNX4k9jYRF/jPzkk63DFDU1wC9+ERu7FMWlqCNX4k/79hSbalhI4vEwzgwAl13G4wKFrbxeFuIccUTcTI0J1dWUv/3sM2uJ3kRn61aGv66+mrrsVVVOW5Ty6GKn4gzffsuUv7Iybjk5QO/e7N3o7/qzaxfw4IMsqfd6ma88blz4aYJ+tm6lpvjmzWwGcf75jTcVjiXvv89epX7n5/MBb70VXiFSIrBgARsoV1cz9JWbC3TrxgwjXeiNOZq1oiQe5eV0Yps3M/1w0CD7ezfOn89ZfKDj6d6dDYCjkVn1N5pozhjbt1NfvaHeSX4+P2wSvYCmthbo0IHpoIHk5LAJ8x13OGNXChHKkWtoRXGOnBzgkksoQHXyyfY78dpa4NJLmcLoXzj1Z8f8+9+RjfnDD5zV5+dTRvfkk1muHw4vv2ytAV5bC8yYEZk98WTt2uAiKKD+IrXiCOrIleTlq6+slfnKyiJzPBUVwAknMP2xuprb4sXAgAHWqoINKSys33vUT2UlsHNn8+2JNzk5oZtRWOmtKHFDHbmSvGRnh3Y8X37Jzj/N6bn59tusRg1coKytpRN//fWmzx882Dp8kpFB/ZdE59BD2Qmo4ZuTz8f1C8Ux1JErycthhwGdO4cO2axYwc5Da9eGN9769dYz7+Li8MIrp50GDBxYf1HQ5+Pi67HHhmeD07z5JjVv8vLqBLKGDavLNlIcwa5Wb0OMMd8YY9YZY3TFQ0kMjKHjads2dEZFRQXw97+HN94xx1iHEPLy+LNw7Jk1i/H5QYPo2P/zH2DKlPCunwh0787F6alTqb++dCm/TgTJhBQm6qwVY0w6gG8BnAFgC4ClAC4VkTWhztGsFSWuVFbS6fzpT4yPN6R3b+Dzz5sep6aGXYG++aZu8TQri5koq1eHlrZVFJuIZdZKPwDrRGSDiFQCeAXAMBvGVRR7yMoCrrzSusFwejqdczikpzNtcexYoHVrdhr69a/ZHk6duOIgdjjyDgACxS+27N9XD2PMWGPMMmPMssLCQhsuqyjNoF07CnU1zPvOyQFuvz38cfLzKf+6YwczTZ58knrmiuIgcQtsicizItJXRPq2VdF5xQmeeYY5661bcwY9YAArFbt3d9qy2FBR0XSfznhSWMj1gGnT2GVJsQ07HPlWAJ0Cvu+4f5+iJBYZGcB993E2XVXFkEjfoHCjuykqYugnO5tvG14vF1WdVoycOJEZRNdeS42Wgw5ityLFFuxY7MwAFztPAx34UgCjROSrUOfoYqeiBLB7N7M+CgqiG6emhmmMq1cH/6xjR6ZPBoqQxYvvvgOOPjq4GMrj4QdM69bxt8mlxGyxU0SqAfwewBwAawG81pgTVxRlP2vW8I2gfXvG8AcNAjZtiny8d9+lGJkVO3eyoMkJpk2zVnlMS6PWjhI1tiy1i8g7AN6xYyxFSQn27QNOPJFdkvxvxR9/zIKh77+PTJ1x+fLQMfHycmDdusjtjYaysuBuTwCdu1U6qNJsNItfUZxg2jTmtweGNmtq6OBnzYpszK5d6ySAG5KdzfCGEwwbFlqLZejQ+NqSpKgjVxQnWLfOWtCrogLYuDGyMS+6KLQU7iGHAGeeGdm40XL88cCYMayuNYYhFa8XGD+e2i1K1GgVg6I4Qb9+dLrFxfX3Z2WFX6DUEK+X4ZlLL6WOjAiLmC65BHjiieY35LALY4CnnmIe/6uvMmw0enTyZQw5iDaWUJRIEaGWy/PPMwZ8+eXAyJHhOcyqKoY6NmxgiAVgWOTYY4GPPopem333bo7RokV04ygJRaisFZ2RK0qk/PrXwGuv1YVIFi/mjPOtt5p2xJmZlNC97z6ek54O/OpXwJ132tNgQ6tNUwqdkStKJKxaxSYTDWVtfT5g9mx2DlIUm9FWb4piJ++/b51SV1ICzJ0bf3uUlEYdueJu1q4F5s1j2X08adnSOtc7J0crFZW4o45ccSc7dwL9+zPz4cILgU6d2MU9XqHCESOsY9lpaczOUJQ4oo5ccSf+FLvSUirplZcDjz/OQpt4UFAAvPMOZ9/5+dwKCoA33gAOOCA+NtjFunXAVVcBPXsCw4cDn33mtEVKM9HFTsV9FBZyBm5Vjt6nDxDPv63qamaf1NRw8dMJUapo+OoryvmWlvIejGEV5vTpwNlnO22d0gBNP1SShz17KElr5ch37YqvLRkZwEknxfeadnLbbSxK8k/oROjUr72Wmi92pEIqMUdDK4r7OOSQ4E4/ABcfdRbZPBYvtl5X+PFHfmAqrkAdueI+0tPZ7cfrrevenpPDHpp33eWsbW6jTRvr/WlpzIlXXIE6csWdDB/O2eRll1EOdvx44Msv3bfQ6DS33hr8duPxsMrUbfH+FEZj5Ip7OfZY4MUXnbbC3Vx9NdUWH3uMjruigrKzEyY4bZnSDDRrRVEUpnCuX8+WcO3aOW2NEoKYlOgbYy4yxnxljKk1xqgmpaK4lYICyueqE3cl0cbIvwQwAsAiG2xRFEVRIiCqGLmIrAUAo7mmiqIojhG3rBVjzFhjzDJjzLLCwsJ4XVZRFCXpaXJGboyZB8Aqp+tOEZkZ7oVE5FkAzwJc7AzbQkVRFKVRmnTkInJ6PAxRFEVRIkMLghRFUVxOtOmHw40xWwAMADDbGDPHHrMURVGUcIk2a+VNAG/aZIuiOENhITBpEnW5Bw4ELr6Y2i2K4hK0RF9JbVasAE45hbriZWXA1KnA/fezuYJ2oldcgsbIldRm9GigqIhOHGDz5B9+AP70J2ftUpRmoI5cSV22bwc2bAjeX1kJvPZa/O1RlAhRR66kLpmZoZs1Z2fH1xZFiQJ15Erq0qoVcPzxbFQRiMcD/Pa3ztikKBGgjlxJbaZOpXRrXh4bLHi9wKBBwC23OG2ZooSNZq0oqU2nTtThfu89YNMmoG9foE8fp61SlGahjlxR0tOBIUOctkJRIkZDK4qiKC5HHbmiKIrLUUeuKIrictSRK4qiuBx15IqiKC7HSKjKtlhe1JhCAJvifuHIaQNgh9NG2ITeS+KRLPcBJM+9JOp9dBGRtg13OuLI3YYxZpmI9HXaDjvQe0k8kuU+gOS5F7fdh4ZWFEVRXI46ckVRFJejjjw8nnXaABvRe0k8kuU+gOS5F1fdh8bIFUVRXI7OyBVFUVyOOnJFURSXo448TIwxFxljvjLG1BpjXJOW5McYM8QY840xZp0x5g6n7YkUY8zzxpifjTFfOm1LtBhjOhlj5htj1uz/27rBaZsiwRiTY4z5zBizav99uL7hqTEm3RjzuTFmltO2hIM68vD5EsAIAIucNqS5GGPSATwB4CwARwK41BhzpLNWRcwkAMmiOVsN4GYRORJAfwDjXPp7qQAwWESOAdAbwBBjTH+HbYqWGwCsddqIcFFHHiYislZEvnHajgjpB2CdiGwQkUoArwAY5rBNESEiiwDsctoOOxCRH0Vkxf6vi0DH0cFZq5qPkOL932bu31ybRWGM6QhgKICJTtsSLurIU4MOADYHfL8FLnQYyYwxpiuAYwEscdaSyNgfilgJ4GcA74mIK+9jPxMA3Aag1mlDwkUdeQDGmHnGmC8tNlfOXhV3YIzJBfAGgBtFZJ/T9kSCiNSISG8AHQH0M8b0ctqmSDDGnAPgZxFZ7rQtzUFbvQUgIqc7bUOM2AqgU8D3HffvUxzGGJMJOvGpIjLDaXuiRUT2GGPmg+sYblyQHgjgPGPM2QByAOQbY14SkdEO29UoOiNPDZYCOMwYc7AxJgvAJQDedtimlMcYYwA8B2CtiDzitD2RYoxpa4xpsf9rD4AzAHztrFWRISLjRaSjiHQF/598kOhOHFBHHjbGmOHGmC0ABgCYbYyZ47RN4SIi1QB+D2AOuKD2moh85axVkWGMmQbgEwA9jDFbjDG/dtqmKBgIYAyAwcaYlfu3s502KgIOBDDfGPMFOGl4T0RckbaXLGiJvqIoisvRGbmiKIrLUUeuKIrictSRK4qiuBx15IqiKC5HHbmiKIrLUUeuKIrictSRK4qiuJz/A/WBWch+Qog0AAAAAElFTkSuQmCC\n", 82 | "text/plain": [ 83 | "
" 84 | ] 85 | }, 86 | "metadata": { 87 | "tags": [], 88 | "needs_background": "light" 89 | } 90 | } 91 | ] 92 | }, 93 | { 94 | "cell_type": "markdown", 95 | "metadata": { 96 | "id": "HjwKo9ydE31x" 97 | }, 98 | "source": [ 99 | "#1. Modele" 100 | ] 101 | }, 102 | { 103 | "cell_type": "code", 104 | "metadata": { 105 | "id": "MS4jOZwzfrrU" 106 | }, 107 | "source": [ 108 | "def sigmoid(x):\n", 109 | " return 1 / (1 + np.exp(-x))" 110 | ], 111 | "execution_count": 4, 112 | "outputs": [] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "metadata": { 117 | "id": "N89yRfD7aat-" 118 | }, 119 | "source": [ 120 | "def initialisation(X):\n", 121 | " W = np.random.randn(X.shape[1], 1)\n", 122 | " b = np.random.randn(1)\n", 123 | " return (W, b)" 124 | ], 125 | "execution_count": 5, 126 | "outputs": [] 127 | }, 128 | { 129 | "cell_type": "code", 130 | "metadata": { 131 | "id": "qg9ZFBlYfHGQ" 132 | }, 133 | "source": [ 134 | "def forward_propagation(X, W, b):\n", 135 | " Z = X.dot(W) + b\n", 136 | " A = sigmoid(Z)\n", 137 | " return A" 138 | ], 139 | "execution_count": 6, 140 | "outputs": [] 141 | }, 142 | { 143 | "cell_type": "markdown", 144 | "metadata": { 145 | "id": "SyR7cN5gFl5O" 146 | }, 147 | "source": [ 148 | "#2. Fonction Cout et Gradients" 149 | ] 150 | }, 151 | { 152 | "cell_type": "code", 153 | "metadata": { 154 | "id": "36N1AVywgUy6" 155 | }, 156 | "source": [ 157 | "def log_loss(y, A):\n", 158 | " return 1/len(y) * np.sum(-y * np.log(A) - (1 - y) * np.log(1 - A))" 159 | ], 160 | "execution_count": 16, 161 | "outputs": [] 162 | }, 163 | { 164 | "cell_type": "code", 165 | "metadata": { 166 | "id": "bWcDHOd0hYKc" 167 | }, 168 | "source": [ 169 | "def gradients(X, A, y):\n", 170 | " dW = 1/len(y) * np.dot(X.T, A - y)\n", 171 | " db = 1/len(y) * np.sum(A - y)\n", 172 | " return (dW, db)" 173 | ], 174 | "execution_count": 8, 175 | "outputs": [] 176 | }, 177 | { 178 | "cell_type": "markdown", 179 | "metadata": { 180 | "id": "vonvu9_UGM6x" 181 | }, 182 | "source": [ 183 | "#3. Optimisation (Descente de Gradient)" 184 | ] 185 | }, 186 | { 187 | "cell_type": "code", 188 | "metadata": { 189 | "id": "GWL981CJjPbs" 190 | }, 191 | "source": [ 192 | "def optimisation(X, W, b, A, y, learning_rate):\n", 193 | " dW, db = gradients(X, A, y)\n", 194 | " W = W - learning_rate * dW\n", 195 | " b = b - learning_rate * db\n", 196 | " return (W, b)" 197 | ], 198 | "execution_count": 9, 199 | "outputs": [] 200 | }, 201 | { 202 | "cell_type": "markdown", 203 | "metadata": { 204 | "id": "KveFQtt0H2kB" 205 | }, 206 | "source": [ 207 | "#4. Prédiction et visualisation" 208 | ] 209 | }, 210 | { 211 | "cell_type": "code", 212 | "metadata": { 213 | "id": "ECsDPa2lnfh0" 214 | }, 215 | "source": [ 216 | "def predict(X, W, b):\n", 217 | " A = forward_propagation(X, W, b)\n", 218 | " return A >= 0.5" 219 | ], 220 | "execution_count": 28, 221 | "outputs": [] 222 | }, 223 | { 224 | "cell_type": "code", 225 | "metadata": { 226 | "id": "XP3xoQS1GZkC" 227 | }, 228 | "source": [ 229 | "def visualisation(X, y, W, b):\n", 230 | " resolution = 300\n", 231 | " fig, ax = plt.subplots(figsize=(9, 6))\n", 232 | " ax.scatter(X[:, 0], X[:, 1], c=y, s=50, edgecolor='k')\n", 233 | "\n", 234 | " #limites du graphique\n", 235 | " xlim = ax.get_xlim()\n", 236 | " ylim = ax.get_ylim()\n", 237 | "\n", 238 | " # meshgrid\n", 239 | " x1 = np.linspace(xlim[0], xlim[1], resolution)\n", 240 | " x2 = np.linspace(ylim[0], ylim[1], resolution)\n", 241 | " X1, X2 = np.meshgrid(x1, x2)\n", 242 | "\n", 243 | " # assembler les 2 variables\n", 244 | " XX = np.vstack((X1.ravel(), X2.ravel())).T\n", 245 | "\n", 246 | " # Prédictions\n", 247 | " Z = predict(XX, W, b)\n", 248 | " Z = Z.reshape((resolution, resolution))\n", 249 | "\n", 250 | " ax.pcolormesh(X1, X2, Z, zorder=0, alpha=0.1)\n", 251 | " ax.contour(X1, X2, Z, colors='g')" 252 | ], 253 | "execution_count": 32, 254 | "outputs": [] 255 | }, 256 | { 257 | "cell_type": "markdown", 258 | "metadata": { 259 | "id": "_ZIYHzIyIASN" 260 | }, 261 | "source": [ 262 | "#5. Modele final" 263 | ] 264 | }, 265 | { 266 | "cell_type": "code", 267 | "metadata": { 268 | "id": "Clu3dOgHmS64" 269 | }, 270 | "source": [ 271 | "def regression_logistique(X, y, learning_rate=0.1, n_iter=100):\n", 272 | " \n", 273 | " # Initialisation\n", 274 | " W, b = initialisation(X)\n", 275 | " loss_history = []\n", 276 | "\n", 277 | " # Entrainement\n", 278 | " for i in range(n_iter):\n", 279 | " A = forward_propagation(X, W, b)\n", 280 | " loss_history.append(log_loss(y, A))\n", 281 | " W, b = optimisation(X, W, b, A, y, learning_rate=0.1)\n", 282 | "\n", 283 | " # Prediction\n", 284 | " visualisation(X, y, W, b)\n", 285 | " plt.figure(figsize=(9, 6))\n", 286 | " plt.plot(loss_history)\n", 287 | " plt.xlabel('n_iteration')\n", 288 | " plt.ylabel('Log_loss')\n", 289 | " plt.title('Evolution des erreurs')" 290 | ], 291 | "execution_count": 33, 292 | "outputs": [] 293 | }, 294 | { 295 | "cell_type": "code", 296 | "metadata": { 297 | "id": "Vv9snZjqGo7v", 298 | "outputId": "8923c469-c9a8-414e-978f-491ca7eb42b8", 299 | "colab": { 300 | "base_uri": "https://localhost:8080/", 301 | "height": 762 302 | } 303 | }, 304 | "source": [ 305 | "regression_logistique(X, y)" 306 | ], 307 | "execution_count": 34, 308 | "outputs": [ 309 | { 310 | "output_type": "display_data", 311 | "data": { 312 | "image/png": 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\n", 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\n", 326 | "text/plain": [ 327 | "
" 328 | ] 329 | }, 330 | "metadata": { 331 | "tags": [], 332 | "needs_background": "light" 333 | } 334 | } 335 | ] 336 | }, 337 | { 338 | "cell_type": "code", 339 | "metadata": { 340 | "id": "DQnDXNrMGq7H" 341 | }, 342 | "source": [ 343 | "" 344 | ], 345 | "execution_count": null, 346 | "outputs": [] 347 | } 348 | ] 349 | } -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Regression-logistique-numpy --------------------------------------------------------------------------------